Ongoing improvements in AI, particularly concerning deep learning techniques, are
assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the …

With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …

Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …

Deep learning, a state-of-the-art machine learning approach, has shown outstanding
performance over traditional machine learning in identifying intricate structures in complex …

Electroencephalography (EEG) motor imagery (MI) signals have recently gained a lot of
attention as these signals encode a person's intent of performing an action. Researchers …

Recently, deep learning has unlocked unprecedented success in various domains,
especially using images, text, and speech. However, deep learning is only beneficial if the …

The tremendous success of machine learning algorithms at image recognition tasks in
recent years intersects with a time of dramatically increased use of electronic medical …

Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …

The goal of the present study was to apply deep learning algorithms to identify autism
spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the …

Rapid advances in hardware-based technologies during the past decades have opened up
new possibilities for life scientists to gather multimodal data in various application domains …